Load and aggregate RHEAS simulated Leaf Area Index (LAI), Water stress and Grain Weight Average Dry (GWAD) across different ensembles. Extract year from dates (we will use harvest year).
Aggregate RHEAS production forecasts and metrics with respect to Districts maize growing calendar.
We assume two maize growing seasons in Tanzania: 1) Season 1: Short Rain Short Dry (SRSD) October – February. 2) Season 2: Long Rain Long Dry Season March – September.
So we will aggregate the metrics and yield forecast per district with
this condition using the function RH_metrics.
Convert RHEAS yields from kg/ha to MT/ha.
Add shapefile for visualization.
## Warning: multiple methods tables found for 'approxNA'
Check and format District names to be consistent in both the RHEAS and administrative boundaries.
## character(0)
Merge RHEAS and Admin data.
Visualize RHEAS predicted yields spatially for season 1. NOTE: Ignore yields over the lake area.
## Warning: multiple methods tables found for 'crop'
## Warning: multiple methods tables found for 'extend'
The first season seems to do well on average.
Now lets how season 2 looks spatially
Visualize trends for the last 5 years.
## Warning: package 'ggplot2' was built under R version 4.1.3